CN113313370A - Enterprise production resource reasonable allocation cloud manufacturing method based on processing and manufacturing granularity - Google Patents
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Abstract
The invention discloses an enterprise production resource reasonable configuration cloud manufacturing method based on processing and manufacturing granularity. After the supply side enterprise fills all manufacturing resource information of the supply side enterprise on the cloud manufacturing platform, the cloud platform correspondingly converts the manufacturing resources of the enterprise into N processing and manufacturing granularities. The enterprise needing outsourcing issues and decomposes outsourcing tasks on the cloud platform and correspondingly converts the outsourcing tasks into required processing and manufacturing granularity, the cloud platform is scheduled according to the processing types and the processing and manufacturing granularity of the enterprise and the tasks, one enterprise can receive a plurality of subtasks for processing at the same time, and the full utilization and reasonable configuration of enterprise manufacturing resources are fully achieved.
Description
Technical Field
The invention relates to the technical field of cloud manufacturing, in particular to a cloud manufacturing method for reasonably allocating enterprise production resources based on processing and manufacturing granularity.
Background
The manufacturing industry has been receiving attention from all countries as an important component in the global industrial structure, and in recent years, with the rapid development of global informatization, the concept and form of cloud manufacturing have come into play. Cloud manufacturing is used as a combination of traditional manufacturing industry and advanced information technology, and manufacturing resources and manufacturing capacity sharing among different enterprises are achieved. The cloud manufacturing method realizes digital packaging and integration and release of manufacturing resources and manufacturing capacity of different enterprises through an informatization technology, solves the problem of uneven distribution of manufacturing resources, solves the problem of resource shortage of small and medium-sized enterprises, and solves the problems of low resource utilization and long-term idle of large enterprises.
Cloud manufacturing is mainly composed of three roles, namely a supply-side service provider, a demand-side service provider and a cloud manufacturing platform. The different service providers at the supply side can process different services with different scales and types because of different enterprise scales, different manufacturing resources and different manufacturing capabilities. At present, a common cloud manufacturing method is that an enterprise encapsulates own manufacturing resources and then enters a cloud platform resource pool to wait for allocation and release of tasks. In the method, each enterprise can only receive one task, and for enterprises with larger scale and more resources, the resources occupied by processing the task are eliminated and the residual resources exist, so that the idle and waste of enterprise processing resources are caused.
Disclosure of Invention
The invention provides an enterprise production resource reasonable allocation cloud manufacturing method based on processing and manufacturing granularity, which is a brand new cloud manufacturing method aiming at the problem that redundant processing resources are idle and wasted after an enterprise with more manufacturing resources receives a subtask.
An enterprise production resource reasonable allocation cloud manufacturing method based on processing and manufacturing granularity mainly comprises the following steps:
step 1: the enterprise fills all the manufacturing information of the enterprise on the cloud manufacturing platform;
and processing resources and processing types of the human resources, the equipment resources, the software resources and the material resources owned by the enterprise are filled and reported by the enterprise on the cloud platform according to the platform resource description rule. The resources are described in detail as follows:
human resources: the cloud manufacturing platform takes the number of people as a measuring unit.
Equipment resources: the equipment machine required by machining and manufacturing is divided into two types of common machine tools and numerically-controlled machine tools (the machine tools are general names of grinding machines, milling machines, drilling machines, lathes and the like), and as the machining capacity of the numerically-controlled machine tools is higher than that of the common machine tools, 1 numerically-controlled machine tool can be converted into 2 common machine tools in terms of machining capacity, and the number of the numerically-controlled machine tools is taken as a metering unit of a cloud manufacturing platform.
Software resources: and processing and manufacturing required software, wherein the cloud manufacturing platform takes the number of the software as a metering unit.
Material resources: processing and manufacturing required blanks, raw materials and the like, wherein the cloud manufacturing platform takes the unit cubic meter blank as a metering unit.
Step 2: correspondingly converting enterprise manufacturing resources into n processing and manufacturing granularities;
the present invention defines the process fabrication particle size as: the processing and manufacturing resources consumed by enterprises for processing unit cubic meter blanks.
The cloud manufacturing platform is converted into the corresponding processing granularity of the enterprise through a formula, wherein the conversion formula is in the following form:
x numerical control machine tool + Y individuals + Z pieces of software + R unit cubic meter blanks as N processing particle sizes
And step 3: the enterprise needing outsourcing issues and decomposes outsourcing tasks on the cloud platform and correspondingly converts the outsourcing tasks into the required processing and manufacturing granularity;
and uploading the processing total task to a cloud manufacturing platform by an enterprise needing outsourced processing, dividing and decomposing the processing total task according to the functional module and the product structure of the product to be processed after uploading the total task to the cloud manufacturing platform, decomposing the same type of components on the same module or part into subtasks of the same grade to perform task decomposition, decomposing the total task into a plurality of subtasks, and filling the processing and manufacturing granularity of the subtasks and selecting the processing type by the enterprise according to the conversion formula in the step 2.
And 4, step 4: the cloud platform carries out scheduling according to the processing types and the processing and manufacturing granularities of enterprises and tasks;
the cloud manufacturing platform carries out primary matching scheduling according to the machinable type of each enterprise, the owned machining and manufacturing granularity, the machining type of the subtasks and the required granularity, the matching principle is that the machining types are the same, the machining and manufacturing granularity of the enterprises is larger than the machining and manufacturing granularity required by the subtasks, and only one subtask is matched with one enterprise in the primary matching scheduling. And after the primary matching is finished, if the remaining subtasks are not distributed for re-matching scheduling, the matching principle is that the processing types are the same and the remaining processing and manufacturing granularity of the enterprise is larger than the processing and manufacturing granularity required by the subtasks, and the matching is carried out for multiple times until the subtasks are completely matched or the remaining granularity and the types of the platform enterprise are not enough to match the remaining subtasks. And after the enterprise finishes processing the current subtask, the processing and manufacturing granularity occupied by the task is released into the resource pool, and a new task is rescheduled and matched.
The invention classifies and defines the manufacturing resources directly related to processing of a supply side enterprise, and provides a conversion presentation form for packaging the manufacturing resources of the enterprise into processing and manufacturing granularity. After the platform decomposes the tasks released by the enterprise on the demand side into subtasks, the subtasks are matched with the resources of the enterprise on the supply side in the mode of processing and manufacturing granularity. And if the enterprise finishes matching one subtask and continues matching the subtask if the redundant processing and manufacturing granularity remains, one enterprise can receive a plurality of subtasks for processing at the same time.
Drawings
The invention is further described with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flow chart of a manufacturing method for reasonably allocating cloud production resources of an enterprise based on processing and manufacturing granularity according to the present invention;
FIG. 2 is a scheduling flow diagram of a cloud manufacturing platform;
Detailed Description
As shown in fig. 1, the method for manufacturing the cloud with reasonable allocation of enterprise production resources based on the processing and manufacturing granularity provided by the invention mainly comprises the following steps:
step 1: the method comprises the following steps that a supply side enterprise fills all manufacturing information of the supply side enterprise on a cloud manufacturing platform;
and processing resources and processing types of the human resources, the equipment resources, the software resources and the material resources owned by the enterprise are filled and reported by the enterprise on the cloud platform according to the platform resource description rule.
Step 2: the cloud platform correspondingly converts the enterprise manufacturing resources into N processing and manufacturing granularities;
the cloud manufacturing platform is converted into the corresponding processing and manufacturing granularity of the enterprise through a formula, wherein the conversion formula is in the following form:
x numerical control machine tool + Y individuals + Z pieces of software + R unit cubic meter blanks as N pieces of processing and manufacturing granularity
And step 3: the enterprise needing outsourcing issues and decomposes outsourcing tasks on the cloud platform and correspondingly converts the outsourcing tasks into the required processing and manufacturing granularity;
and uploading the processing total task to a cloud manufacturing platform by an enterprise needing outsourced processing, dividing and decomposing the processing total task according to the functional module and the product structure of the product to be processed after uploading the total task to the cloud manufacturing platform, decomposing the same type of components on the same module or part into subtasks of the same grade to perform task decomposition, decomposing the total task into a plurality of subtasks, and filling the processing and manufacturing granularity of the subtasks and selecting the processing type by the enterprise according to the conversion formula in the step 2.
And 4, step 4: the cloud platform carries out scheduling according to the processing types and the processing and manufacturing granularities of enterprises and tasks;
as shown in fig. 2, the cloud manufacturing platform decomposes the subtasks in the resource pool and the filled enterprises to perform initial matching scheduling according to the processing type and the processing and manufacturing granularity, the matching principle is that the processing type is the same and the processing and manufacturing granularity of the enterprises is larger than the processing and manufacturing granularity required by the subtasks, and only one subtask is matched by one enterprise in the initial matching scheduling. And after the primary matching is finished, if the remaining subtasks are not distributed for re-matching scheduling, the matching principle is that the processing types are the same and the remaining processing and manufacturing granularity of the enterprise is larger than the processing and manufacturing granularity required by the subtasks, and the matching is carried out for multiple times until the subtasks are completely matched or the remaining granularity and the types of the platform enterprise are not enough to match the remaining subtasks. And after the enterprise finishes processing the current subtask, the processing and manufacturing granularity occupied by the task is released into the resource pool, and a new task is rescheduled and matched.
And 5: the product is delivered after being processed;
after the product processing is finished, the supply side enterprise gives the demand side enterprise, the processed product is evaluated, and the priority of the next order receiving of the supply side enterprise is influenced by the level of the evaluation coefficient.
Claims (5)
1. An enterprise production resource reasonable allocation cloud manufacturing method based on processing and manufacturing granularity is characterized by comprising the following steps:
step 1: the enterprise fills all the manufacturing information of the enterprise on the cloud manufacturing platform;
processing resources and processing types of the human resources, the equipment resources, the software resources and the material resources owned by the enterprise are filled and reported by the enterprise on the cloud platform according to the platform resource description rule;
step 2: correspondingly converting enterprise manufacturing resources into N processing and manufacturing granularities;
the cloud manufacturing platform is converted into the corresponding processing granularity of the enterprise through a formula, wherein the conversion formula is in the following form:
x numerical control machine tool + Y individuals + Z pieces of software + R unit cubic meter blanks as N pieces of processing and manufacturing granularity
And step 3: the enterprise needing outsourcing issues and decomposes outsourcing tasks on the cloud platform and correspondingly converts the outsourcing tasks into the required processing and manufacturing granularity;
the enterprise needing outsourced processing uploads a processing total task to the cloud manufacturing platform, the total task is decomposed according to the decomposition rule of the cloud platform after being uploaded to the cloud manufacturing platform, the total task is decomposed into a plurality of subtasks, and the enterprise carries out processing and manufacturing granularity filling of the subtasks and selection of processing types according to a conversion formula;
and 4, step 4: the cloud platform carries out scheduling according to the processing types and the processing and manufacturing granularities of enterprises and tasks;
the cloud manufacturing platform firstly carries out primary matching scheduling according to the machinable type of each enterprise, the possessed machining and manufacturing granularity, the machining type of the subtasks and the required granularity, the matching principle is that the machining types are the same, the machining and manufacturing granularity of the enterprises is larger than the machining and manufacturing granularity required by the subtasks, and only one subtask is matched with one enterprise in the primary matching scheduling; after the primary matching is finished, if the remaining subtasks are not distributed for carrying out re-matching scheduling, the matching principle is that the processing types are the same, the remaining processing and manufacturing granularity of the enterprise is larger than the processing and manufacturing granularity required by the subtasks, and the matching is carried out for multiple times until the subtasks are completely matched or the remaining granularity and the types of the platform enterprise are not enough to match the remaining subtasks; and after the enterprise finishes processing the current subtask, the processing and manufacturing granularity occupied by the task is released into the resource pool, and a new task is rescheduled and matched.
2. The enterprise production resource rational allocation cloud manufacturing method based on the processing and manufacturing granularity according to claim 1, characterized in that: the human resources, equipment resources, software resources and material resources described in step 1 are specifically described as follows:
human resources: processing and manufacturing directly related personnel, wherein the cloud manufacturing platform takes the number of people as a metering unit;
equipment resources: the equipment machine required by machining and manufacturing is characterized in that all machining equipment is divided into two types of common machine tools and numerically-controlled machine tools, and the machining capacity of the numerically-controlled machine tools is higher than that of the common machine tools, so that 1 numerically-controlled machine tool can be converted into 2 common machine tools in terms of machining capacity, and the number of the numerically-controlled machine tools is used as a metering unit by a cloud manufacturing platform;
software resources: processing and manufacturing required software, wherein the cloud manufacturing platform takes the number of the software as a metering unit;
material resources: processing and manufacturing required blanks, raw materials and the like, wherein the cloud manufacturing platform takes the unit cubic meter blank as a metering unit.
3. The enterprise production resource rational allocation cloud manufacturing method based on the processing and manufacturing granularity as claimed in claim 2, characterized in that: the manufacturing granularity stated in step 2 is defined as the enterprise manufacturing resources consumed by the enterprise to process a unit cubic meter of the blank.
4. The enterprise production resource rational allocation cloud manufacturing method based on the processing and manufacturing granularity according to claim 1, characterized in that: and 3, dividing and decomposing the cloud manufacturing platform decomposition rule according to the functional module and the product structure of the product to be processed, and decomposing the same type of components on the same module or part into subtasks of the same grade.
5. The enterprise production resource rational allocation cloud manufacturing method based on the processing and manufacturing granularity according to claim 1, characterized in that: in the matching process of the enterprise and the subtasks in the step 4, the processing type is the first matching priority, and the matching of the processing and manufacturing granularity is performed after the processing type is matched.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113902027A (en) * | 2021-10-22 | 2022-01-07 | 上海理工大学 | Integrity model resource matching method based on multi-level label K nearest neighbor |
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| CN109726926A (en) * | 2019-01-02 | 2019-05-07 | 重庆大学 | Machine tool equipment resource supply and demand matching process based on Grey Relation Algorithm under a kind of constraint of multivariate quality |
| CN110059942A (en) * | 2019-04-02 | 2019-07-26 | 南京邮电大学 | A kind of cloud manufacturing recourses service Optimization Scheduling based on fuzzy multiobjective optimization |
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Patent Citations (5)
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| CN106572187A (en) * | 2016-11-11 | 2017-04-19 | 三维通信股份有限公司 | Cloud manufacturing service scheduling method and system |
| CN107944698A (en) * | 2017-11-22 | 2018-04-20 | 重庆大学 | The manufacture demand of facing cloud manufacture and capacity of equipment normalization modeling method |
| CN108320105A (en) * | 2018-02-09 | 2018-07-24 | 广东原尚物流股份有限公司 | Logistics prestowage dispatching method, device, storage medium and terminal device |
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